With the rapid development of the mobile communication technology, mobile trajectories of
humans are massively collected by Internet service providers (ISPs) and application service …

Accurate human mobility prediction is important for many applications in wireless networks,
including intelligent content caching and prefetching, network optimization, etc. However …

Personalized prediction of responses for individual entities caused by external drivers is vital
across many disciplines. Recent machine learning (ML) advances have led to new state-of …

Accurately predicting human mobility is crucial for various applications, eg, transportation
services, epidemic control, and advertisement recommendation. Although numerous …

Nowcasting the vehicular delay at intersections of road networks not only optimizes the
signal timing at the intersections, but also alleviates traffic congestion effectively. Existing …

Bicycle-sharing systems play an essential role in the transportation system of urban cities
due to their outstanding advantages such as more convenience and less pollution. The …

Human mobility behaviour is far from random and can be predictable. Predicting human
mobility behaviour has the potential to improve location selection for facilities, transportation …

Both app developers and service providers have strong motivations to understand when and
where certain apps are used by users. However, it has been a challenging problem due to …

Understanding intra-urban human mobility patterns and their potential driving forces are vital
to city planning and commercial site selection. In this paper, we first investigate the functions …

Sparse trajectory data are trajectories that cover a relatively large geographic area with
infrequent samplings of movements, such as human migration and hurricane trajectories …